WildfireRiskFinder

Camilla, GA

Camilla wildfire risk explained

High
61stpercentile nationally

Camilla's 2,496 buildings earn a 61st-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Camilla at the 62nd national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.

Where Camilla's buildings actually sit

2,496Total buildings
40.4%Direct exposure
54.8%Indirect exposure
4.9%Minimal exposure

Indirect exposure is dominant in Camilla (54.8% of 2,496 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 40.4% sit in the Direct zone.

How Camilla compares

Camilla's 61st national percentile looks worse in isolation than its 25th ranking inside Georgia does — this place is on the milder end for its own state, by 37 points. Among the 31,521 US communities USFS scores, Camilla ranks 12,188 for wildfire risk (1 is highest) and 6,302 by building count (1 is largest). Within Georgia alone, it ranks 503 of 669 places by risk. See the full county-by-county picture for Georgia on its state page.

What this risk score means for insurance

Camilla's high rating (61st percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.

Hardening a home in Camilla

Because 54.8% of Camilla's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.

Where Camilla's figures come from

Every one of the two percentiles behind Camilla's 12,188-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Camilla's dominant indirect exposure actually means, with real examples from across the dataset.